2 Copyright (C) 2008-2015 EDF R&D
4 This file is part of SALOME ADAO module.
6 This library is free software; you can redistribute it and/or
7 modify it under the terms of the GNU Lesser General Public
8 License as published by the Free Software Foundation; either
9 version 2.1 of the License, or (at your option) any later version.
11 This library is distributed in the hope that it will be useful,
12 but WITHOUT ANY WARRANTY; without even the implied warranty of
13 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
14 Lesser General Public License for more details.
16 You should have received a copy of the GNU Lesser General Public
17 License along with this library; if not, write to the Free Software
18 Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
20 See http://www.salome-platform.org/ or email : webmaster.salome@opencascade.com
22 Author: Jean-Philippe Argaud, jean-philippe.argaud@edf.fr, EDF R&D
33 One ADAO case is defined by a set of data and of choices, packed together
34 through the user interface of the module. The data are physical
35 measurements that have technically to be available before or during the
36 case execution. The simulation code(s) and the data assimilation or
37 optimization method, and their parameters, has to be chosen, they define
38 the execution properties of the case.
41 One iteration occurs when using iterative optimizers (e.g. 3DVAR), and it
42 is entirely hidden in the main YACS OptimizerLoop Node named
43 "*compute_bloc*". Nevertheless, the user can watch the iterative process
44 through the "*YACS Container Log*" window, which is updated during the
45 process, and using "*Observers*" attached to calculation variables.
48 Keyword to indicate the covariance matrix of *a posteriori* analysis
51 BMA (Background minus Analysis)
52 Difference between the background state and the optimal state estimation,
53 noted as :math:`\mathbf{x}^b - \mathbf{x}^a`.
55 OMA (Observation minus Analysis)
56 Difference between the observations and the result of the simulation based
57 on the optimal state estimation, the analysis, filtered to be compatible
58 with the observation, noted as :math:`\mathbf{y}^o -
59 \mathbf{H}\mathbf{x}^a`.
61 OMB (Observation minus Background)
62 Difference between the observations and the result of the simulation based
63 on the background state, filtered to be compatible with the observation,
64 noted as :math:`\mathbf{y}^o - \mathbf{H}\mathbf{x}^b`.
67 Keyword to indicate the Desroziers-Ivanov parameter measuring the
68 background part consistency of the data assimilation optimal state
69 estimation. Its value can be compared to 1, a "good" estimation leading to
70 a parameter "close" to 1.
73 Keyword to indicate the Desroziers-Ivanov parameter measuring the
74 observation part consistency of the data assimilation optimal state
75 estimation. Its value can be compared to 1, a "good" estimation leading to
76 a parameter "close" to 1.
78 MahalanobisConsistency
79 Keyword to indicate the Mahalanobis parameter measuring the consistency of
80 the data assimilation optimal state estimation. Its value can be compared
81 to 1, a "good" estimation leading to a parameter "close" to 1.
84 The optimal state estimation through a data assimilation or optimization
88 The *a priori* known state, which is not optimal, and is used as a rought
89 estimate, or a "best estimate", before an optimal estimation.
92 Difference between the observations and the result of the simulation based
93 on the background state, filtered to be compatible with the observation.
94 It is similar with OMB in static cases.
97 Keyword to indicate the minimization function, noted as :math:`J`.
100 Keyword to indicate the observation part of the minimization function,
101 noted as :math:`J^o`.
104 Keyword to indicate the background part of the minimization function,
105 noted as :math:`J^b`.